Abstract:With the popularity of renewable energy, microgrids have become an important tool for sustainable energy supply. However, due to its source-load uncertainty and carbon emission challenges, optimal scheduling has become a difficult problem. In this paper, a multi-time scale robust optimal scheduling method based on liquid storage carbon capture and storage and demand response is proposed to reduce the carbon emission of microgrids and improve their operation performance. This method schedules at a time interval of 1 hour in the day-ahead stage, uses robust optimization to deal with the low-frequency components of uncertainty, and combines carbon capture technology and demand response to promote the low-carbon economy of the scheduling plan. In the intra-day stage, the scheduling is carried out at a 15-minute interval. The model predictive control is used to track and scroll the day-ahead robust economic scheduling plan to deal with the high-frequency components of source-load prediction error and uncertainty, so as to ensure the actual power balance of the microgrid. The simulation analysis shows that this method can significantly reduce the total cost and carbon emissions of the microgrid, and improve the operation performance and sustainability of the microgrid.